Cooperative Transmission for a Vector Gaussian Parallel Relay Network

In this paper, we consider a parallel relay network where two relays cooperatively help a source transmit to a destination. We assume the source and the destination nodes are equipped with multiple antennas. Three basic schemes and their achievable rates are studied: Decode-and-Forward (DF), Amplify-and-Forward (AF), and Compress-and-Forward (CF). For the DF scheme, the source transmits two private signals, one for each relay, where dirty paper coding (DPC) is used between the two private streams, and a common signal for both relays. The relays make efficient use of the common information to introduce a proper amount of correlation in the transmission to the destination. We show that the DF scheme achieves the capacity under certain conditions. We also show that the CF scheme is asymptotically optimal in the high relay power limit, regardless of channel ranks. It turns out that the AF scheme also achieves the asymptotic optimality but only when the relays-to-destination channel is full rank. The relative advantages of the three schemes are discussed with numerical results.Comment: 35 pages, 10 figures, submitted to IEEE Transactions on Information Theor

Capacity bounds for some Gaussian interference channels

In current wireless networks, co-channel interference is the major limiting factor in achieving high spectral efficiency. The effective interference at receivers can be minimized by using advanced interference management techniques. Given channel conditions, what is the fundamental limit on maximum spectral efficiency we can achieve, and which encoding and decoding techniques achieve this limit? These research questions can be addressed as network information theory problems. In particular, the capacity of Gaussian interference channels is an important open problem dealing with these fundamental questions. Some special cases of the interference channels and their capacity regions are studied in this dissertation. For a class of partially connected interference channels, approximate capacity regions are characterized. The impact of topology, interference alignment, and the interplay between interference and noise are discussed. The results show that for these channels, genie-aided outer bounds are tight to within a constant gap from capacity. Near-optimal achievable schemes, based on rate-splitting and lattice alignment, are presented. The Gaussian X-channel is also an important Gaussian interference channel model. Lower and upper bounds on the sum-rate capacity are derived for this channel. The achievable schemes are based on layered lattice coding and compute-and-forward decoding. For different regimes of channel parameters, some combinations of encoding and decoding strategies are designed. For some range of channel parameters, the approximate sum-rate capacity is characterized to within a constant gap.Electrical and Computer Engineerin